Application of LST Frequency Distribution in Environmental Change Detection in Khuzestan Province(A Case Study: Shadegan, Hawr-al-Azim, and Naseri Wetlands)

In this research, satellite-derived land surface temperature (LST) data from MODIS Aqua were utilized to detect environmental changes in Khuzestan Province, focusing on three wetlands: Shadegan, Hoor-al-Azim, and Naseri, over the period from ۲۰۰۰ to ۲۰۲۰. Initially, the changes in the frequency distribution of LST were computed. Subsequently, applying principal component analysis to the percentage distribution matrix of LSTrevealed that the fourth component (PC۴) reflects changes in water and vegetation cover. Linear regression analysis on the time series of the PC۴ scores unveiled the trends in water and vegetation changes. Long-term mean maps of LST in Shadegan Wetland indicated that the LST is minimally ۲۵ degrees Celsius at night and exceeds ۳۰ degrees during the day. The LST trend map illustrated an increasing trend of approximately ۰.۳ degrees. The map of the PC۴ scores revealed a negative trend in the wetland area, indicating fluctuations in the water level and extensive drying of a significant portion of the wetland. In Hoor-al-Azim Wetland, temperatures during the day exceed ۳۰ degrees, while at night, they range around ۲۵ degrees, with an increasing trend of about ۰.۸ degrees. The LST difference between day and night varies between ۵ to ۱۰ degrees, and the PC۴ scores suggest positive values, signifying the transition from a watery to a dry and salty region. Naseri Wetland exhibits daytime LST exceeding ۳۵ degrees, and nighttime LST surpassing ۲۰ degrees, with an average decreasing trend of ۰.۶ degrees. The day-night LST difference over the twenty-year period ranges between ۱۰ to ۱۵ degrees Celsius, and the PC۴ scores show positivity, indicating an increase in water volume.

Keywords:

Environmental Changes , Land Surface Temperature , Shadegan Wetland , Hoor-al-Azim Wetland , Naseri Wetland , Principal Component Analysis , Trend Analysis